Evidence map›Paper›PMID 42774590›Full record

Article... International Conference on Learning Representations2023

GAMR: A Guided Attention Model for (visual) Reasoning.

Mohit Vaishnav, Thomas Serre

Abstract read
In one paragraph

Article in ... International Conference on Learning Representations, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mohit VaishnavArtificial and Natural Intelligence Toulouse Institute, Université de Toulouse, France.
Thomas SerreArtificial and Natural Intelligence Toulouse Institute, Université de Toulouse, France.

Funding

Brain Science Compute ClusterS10OD025181 · OD · BROWN UNIVERSITY · PI SANES, JEROME N · 2019 to 2019
$600k
NIH HHS S10 OD025181
6 · The paper itself

Abstract

Humans continue to outperform modern AI systems in their ability to flexibly parse and understand complex visual scenes. Here, we present a novel module for visual reasoning, the Guided Attention Model for (visual) Reasoning (

Identifiers

PMID42774590
PMCPMC13594982

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.